Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-29332 is a high-severity Use of Insufficiently Random Values (CWE-330) vulnerability in Microsoft Azure Kubernetes Service. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 14% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Microsoft Azure Kubernetes Service contains an elevation of privilege vulnerability tracked as CVE-2023-29332. The flaw stems from use of insufficiently random values combined with improper input validation, allowing an unauthenticated network attacker to obtain sensitive information from the affected Kubernetes control plane or node components. It carries a CVSS 3.1 score of 7.5 reflecting network attack vector, low complexity, and no required privileges or user interaction.
An attacker with network access can exploit the weakness to read confidential data that would otherwise be restricted, achieving partial elevation of privilege within the Azure Kubernetes Service environment. The vulnerability can be reached without authentication, increasing the potential scope of exposure in multi-tenant or publicly reachable clusters.
Microsoft’s Security Response Center advisory at https://msrc.microsoft.com/update-guide/vulnerability/CVE-2023-29332 provides official guidance on patches and configuration changes required to address the issue. The current EPSS score of 0.1522 with a recorded peak of 0.1953 indicates moderate and sustained exploitation interest following disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-32906
Vulnerability Data
Microsoft Azure Kubernetes Service Elevation of Privilege Vulnerability
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Key generation under controlled management uses approved random-bit sources rather than insufficiently random values.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Cryptographic controls require use of approved, sufficiently random values for keys and nonces.
Secure SDLC processes include verification steps that can catch insufficient randomness but do not directly specify RNG requirements.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Secure coding standards explicitly prohibit use of weak or predictable random number generators.
Security testing can detect weak randomness but does not prescribe the control itself.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.